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DBMS > Citus vs. Google Cloud Spanner vs. LevelDB vs. Splice Machine

System Properties Comparison Citus vs. Google Cloud Spanner vs. LevelDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.citusdata.comcloud.google.com/­spannergithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.citusdata.comcloud.google.com/­spanner/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperGoogleGoogleSplice Machine
Initial release2010201720112014
Current release8.1, December 20181.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Java
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infoQuery statements complying to ANSI 2011noyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication with 3 replicas for regional instances.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standard

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More resources
CitusGoogle Cloud SpannerLevelDBSplice Machine
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